Join the Bugout Slack dev community to connect with fellow data scientists, ML practitioners, and engineers: https://join.slack.com/t/bugou....t-dev/shared_invite/

The GPT-3 language models have a range of impressive capabilities; however, they also have a number of performance limitations.

In this talk OpenAI researcher, Todor Markov, discusses a new fine-tuning API by OpenAI and show examples of how it can be used to create specialized models.

Our speaker – Todor Markov is a researcher on the Applied AI team at OpenAI. His current work focuses on improving the safety & monitoring system for the OpenAI API.

00:09:38 — Introduction Todor Markov to the Bugout community
00:11:12 — Colleges to OpenAI
00:11:36 — GTP-3 & the OpenAI API
00:24:43 — Can GTP-3 make mathematically correct statements?
00:31:11 — OpenAI fine-tuning API
00:41:55 — Questions: sizes of GTP-3 models, size of data sets, technical background of fine tuning, models for improving semantic search, GTP-3 to transfer to texts, chip models, A/B testing model quality, is it expensive. customers, limit of models, ​​tips for people who want to work in AI, plans for meetups

Vídeo rápido sobre como treinar modelos GPT-3 usando api da OpenAI com fine-tuning.

LINKS:
- https://beta.openai.com/docs/guides/fine-tuning
- https://github.com/infoslack/y....outube/tree/main/fin

Patreon: https://www.patreon.com/daveshap (now includes Discord!)
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Relevant Subreddits:
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Heuristic Imperatives: https://www.reddit.com/r/HeuristicImperatives/
Autonomous AI: https://www.reddit.com/r/Autonomous_AI/

DISCLAIMER: This video is not medical, financial, or legal advice. This is just my personal story and research findings. Always consult a licensed professional.

I work to better myself and the rest of humanity.

I hacked my brain with a compact electroencephalogram (EEG) and connected it to GPT-4 with the OpenAI API. In this crazy tutorial, you'll learn how to use JavaScript to read your brainwaves.

#tech #javascript #science

💬 Chat with Me on Discord

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🔗 Resources

Neurosity Crown https://neurosity.co
Brainwaves https://www.scientificamerican.....com/article/what-is
Learn JavaScript Basics https://youtu.be/lkIFF4maKMU
GPT-4 overview https://youtu.be/EunbKbPV2C0

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🎨 My Editor Settings

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How To Use GPT-4 (GPT-4 Tutorial)

GPT-4 is the latest and greatest language processing tool on the market, and in this video, we'll share 10 secret tips and tricks to help you get the most out of this amazing technology.

Our expert team has spent countless hours working with GPT-4, and we're excited to share our insights with you. Whether you're a content creator, researcher, or just curious about the capabilities of GPT-4, these tips and tricks will help you use it more effectively and efficiently.

From creating more natural language output to improving your model's accuracy, our tips will help you take your GPT-4 skills to the next level. So don't miss out on this valuable information! T

Hi, thanks for watching our video about training large language models on PyTorch 2.0
In this video we’ll walk you through:
- GPT4
- GPU
- Multimodal
- LLM
- Model Training
- Model Parallelism
- Distributed Data Parallel DDP
- Deep Learning
- ChatGPT
- palm-e Models
- VALLE
- GOOGLE LAMDA
Mode Parallel, Gradient Accumulation, Data Parallel with PyTorch, Larger Batches

The PyTorch Distributed Stack is a set of PyTorch features that facilitate training models in distributed systems. PyTorch has introduced multiple new features in the distributed package to help support larger scale and higher efficiency for both data and model parallel. In this talk, Yanli Zhao (Software Engineer, Meta AI) shares tips on how to reduce memory footprint, fit larger models and achieve significant speedup with distributed systems with features like Zero Redundancy Optimizer, DistributedDataParallel, FullyShardedDataParallel, CUDA RDMA and ShardedTensor.

OpenAI has officially announced GPT-4 the latest version of its incredibly popular large language model powering artificial intelligence (AI) chatbots. ChatGPT is an AI chatbot that utilizes the language models of GPT-3 and GPT-4 for interactive communication. In other words you can use chatgpt with gpt4. A Generative Pre-Trained Transformer (GPT) is a sophisticated neural network architecture used to train large language models (LLMs). It makes use of large amounts of publicly available Internet text to simulate human communication.

Main improvements:
* It's multimodal (what it is is in video)
* Longer context length
* Better performance
* More safer

chatgpt,
gpt4,
google AI,
Google Lamda,
Google PALM,
artificial intelligence,
Machine learning,
transformer models,
deep learning,
Ray,Ray Tune,Hyperparameter optimization,machine learning,mlflow,open-source

TIMESTAMPS
0:00 Intro
0:55 PyTorch
1:25 Autograd
2:35 PyTorch Distributed
3:10 Types of Parallelization
5:20 DDP
6:38 FSDP
7:48 Fairscale
8:55 PyTorch Lightning
10:30 Model Parallel
11:48 Sagemaker Training



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LINKS/Sources USED:
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#artificialintelligence #gpt4 #chatgpt #Lamda #google #ai #machinelearning #dalle2 #gpt3 #gpt4 #futuretech #futureishere #technology #languagemodels #BIRT #ai #GPT4 #OpenAI #FreeAccess #ArtificialIntelligence #Tutorial

Check out this video to know how you can construct your own chatbot
by giving your own data. As we are feeding our own data and creating a knowledge base, all the responses will be based on our data.

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How-To-Fix:
- GPT_Index ModuleNotFound - https://youtu.be/nKFJHjc9xxU
- ImportModule error: GPTSimpleVectorIndex - https://youtu.be/mwGAb3AgfRM
- All borken changes: https://youtu.be/tU6EmusO43A

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⭐Microsoft Azure: https://www.youtube.com/watch?v=wEG8ZCqs_ls&list=PLb9nVWmuEUuFElg3ZkQhUg157NZtxFeiN

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#chatbot #python #openai

Training Chat GPT with your business information involves providing the model with data specific to your business domain so that it can learn and generate relevant responses. Here are the steps to prepare a note on your business and insert it into the chat area to train Chat GPT:

Prepare a note that contains information about your business, such as its products, services, policies, and procedures. You can write the note in a document or note-taking application.

Identify the keywords and phrases that are relevant to your business and highlight them in the note. These keywords and phrases will help Chat GPT to learn and generate relevant responses.

Open the chat area where you want to train Chat GPT, such as a chatbot or messaging platform.

Copy and paste the note into the chat area. Chat GPT will analyze the text and use it to train its language model.

Interact with Chat GPT by asking it questions related to your business domain. Chat GPT will use its trained model to generate responses based on the information you provided.

Monitor the responses generated by Chat GPT and provide feedback to help it learn and improve. You can also update the note with new information to expand Chat GPT's knowledge base.

Repeat the process of training and interacting with Chat GPT until it can provide accurate and relevant responses to a wide range of questions related to your business domain.
#howto #train #chatgpt #chatgptbot #chatgpttutorial #chatgpthowtouse #chatgptexplained #chatgptprompts

Video Title: How to Train Chat GPT On Your Business | Training Chat GPT on Your own.

Subscribe: https://www.youtube.com/c/EmuB....oss?sub_confirmation

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Email: burhan@pagiest.com
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Disclaimer:
This video is made for the educational purposes. Viewer is solely responsible for all of their actions and implementation. Before doin anything please do consider with a professional expert. This video might also be associated with affiliated links by which the channel could make a potential commission from the company.

Today we look at how to create your own GPT-3 tool in under 60 seconds.
👉 Get Niches$$ here: https://go.aiprofitz.com/nichesss

This is literally so easy anyone can do it!

Is it the most advanced, most amazing use of GPT-3 yet?

Probably not. It is still a pretty amazing offer nonetheless... And it is 100% included in the lifetime deal still available on Appsumo.

👉 Get Niches$$ here: https://go.aiprofitz.com/nichesss

I'd love to hear your ideas down in the comments.

Nichesss will always be one of my favorite GPT-3 tools. I still think it holds up against any on the market, but the long form editor, and overall feel of it is definitely a step behind some of the newer products that have launched.

That being said, the best product is that which you use. I used nichesss a ton starting out. I haven't used it as much since I picked up rytr and as these tools continue to develop, I see nichesss coming back into my arsenal a bit. I hope the community adds unique perspectives and takes it to the next level

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DISCLAIMER: This video and description contain affiliate links, which means that if you click on one of the product links, I’ll receive a small commission at no cost to you. Thanks for supporting this channel by clicking the links in my description!

In today's video I am going to teach you how to create a custom GPT-4 chatbot. In this tutorial you'll discover how to train your model to respond to tweets, questions, or any text data in any personality you choose. With GPT-4's natural language processing, you can make your chatbot sound human-like and engage in intelligent conversations!

💻 Get started with MindsDB today for FREE: https://mindsdb.com/

If you want to automate your chatbot and make it reply automatically to tweets or other information you can use a feature called "JOBS" from MindsDB. JOBS work just like regular cron jobs where you can schedule a task to run every x seconds, minutes, hours etc. you can learn more about it from here: https://docs.mindsdb.com/sql/create/jobs

If you want to contribute to MindsDB here is the link! https://github.com/mindsdb/mindsdb/

💻 Chatbot Guide/Article: https://dev.to/mindsdb/build-a....-celebrity-twitter-c
💻 SnoopStein Twitter: https://twitter.com/snoop_stein/with_replies

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⭐️ Timestamps ⭐️
00:00 | Overview
00:29 | Chatbot Demo
02:25 | MindsDB Setup
04:37 | Making The Chatbot
17:08 | Using The Chatbot From Python
19:26 | Conclusion

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Learn how to get started with the OpenAI API and GPT-3 in this Python Beginner tutorial.

Get your Free Token for AssemblyAI Speech-To-Text API 👇https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_pat_12

OpenAI is known for the creation of the GPT-3 model, a powerful deep learning model capable of producing human-like text.

What makes this API special is not only the powerful model but also that the API is not designed for one use-case only, but instead the API provides a general-purpose “text in, text out” interface, which allows users to try it on virtually any task in the English language.

Resources: https://openai.com/api/
Docs: https://beta.openai.com/docs/
AssemblyAI API tutorial: https://youtu.be/GvfmDGin7Zs

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Timestamps:
00:00 Introduction
00:44 Pricing and Docs
01:34 Python Setup
04:00 Engine
04:42 Completion Endpoint
07:40 Playground
10:57 Classification Endpoint
14:00 Search Endpoint
16:10 Question answering Endpoint
18:57 AssemblyAI + OpenAI Virtual Assistant

#MachineLearning #DeepLearning #Python #OpenAI

In this tutorial you will learn everything you need to fine tune (train) your GPT-2 Model. By training the model on specific texts you can improve the results quality by a large margin. Fine Tuning your GPT-2 Model is quite easy and can be done in a few simple steps.

First you need to download the repository from Github. After that you need to create a training.txt file including the data on which your model should be trained on. The next step is to convert the file into an npz format from which you can then train the model. After the GPT-2 model has been trained you can then copy the files into your final model and just run the sample code.


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HuggingFace Space: https://huggingface.co/spaces/pritish/BookGPT
Kaggle Notebook: https://bit.ly/3kg3dP7

Have you ever wished you could search a book like you search the web? In this video, we'll show you how to build an AI book search using the Universal Sentence Encoder and GPT-3. We'll walk through the steps of breaking down a large book into smaller chunks, generating embeddings for each chunk using the Universal Sentence Encoder, and then using K-nearest neighbors to find the most similar chunks to a user's question. With this approach, you can quickly search through a large corpus of text and find the most relevant information. Finally, we will use GPT3 to generate a concise answer which can also refer page numbers from the book.

Movie Recommendation System: https://youtu.be/pvY0BmAFxwg
(watch this for more info on universal sentence encoder)

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Google Search Video used from 0:19 to 0:21 and 2:04 to 2:12 -
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Thank you,
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In this video, I go over how to create a custom dataset to finetune GPT Neo and GPT-J-6B. To do this, I create an AI quote generator.

Github: https://github.com/mallorbc/GPT_Neo_quotes_dataset

Timestamps

00:00 - Intro
00:29 - Quotes Dataset
01:59 - Code Overview
07:07 - Running The Code
07:54 - Looking At Generated Dataset
08:35 - Running The Fine-tuned Model
09:56 - Outro

Train ChatGPT & GPT-4 For PERFECT Midjourney V5 Images! In this video, I'm gonna show you how you can craft amazing and super creative prompts for Midjourney using ChatGPT and GPT-4! Unleash the full potential of Ai art!

What did you think of this trick? Let me know in the comments!
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Full prompt: https://pastebin.com/8zeBDedK

Previous GPT-4 Secret Prompts video: https://youtu.be/OHdB5sqZMTs


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#GPT4 #GPT3 #ChatGPT #midjourney
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Hello everyone! Today we well be going over how to fine tune OpenAI's Chat-GPT3 using either someone else's data set or out own. We'll first go over how to reformat your data into a Json file and then how to easily reformat it to make sure the AI accepts it and has your input data accepted. After that we'll go over how to use the model!